Tuberculosis (TB) treatment challenges in TB-diabetes comorbid patients: a systematic review and meta-analysis

Abstract Background The Directly Observed Treatment-Short Course (DOTS) Programme was implemented by WHO and includes a combination of four anti-tuberculosis (TB) drugs (isoniazid, pyrazinamide, ethambutol and rifampicin) for a period of six months to eradicate the TB infection completely. Diabetes mellitus (DM) is recognized as one of a strong contributor of TB according to World Health Organization (WHO). The presence of diabetes mellitus type 2 (DM type 2) makes TB treatment complicated. Thus, the objective of the current meta-analysis was to identify and quantify the impact of type 2 DM on treatment outcomes of TB patients treated under the DOTS Programme. Methods This meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Through a systematic review of relevant literature, we focused on studies investigating treatment outcomes including extended treatment duration and recurrence for individuals with both TB and DM undergoing DOTS therapy. The extracted information included study designs, sample sizes, patient characteristics and reported treatment results. Results In 44 studies from different parts of the world, the pooled HR for the impact of DM on extended treatment duration and reoccurrence were HR 0.72, 95% CI 0.56–0.83, p < .01 and HR 0.93, 95% CI 0.70–1.04, p = .08, respectively. The pooled HR for impact of DM on composite TB treatment outcomes was calculated as 0.76 (95% CI 0.60–0.87), p < .01 with an effect size of 41.18. The heterogeneity observed among the included studies was moderate (I2 = 55.79%). Conclusions A negative impact of DM was found on recurrence and extended treatment duration in TB patients treated with DOTS therapy. DM type 2 is responsible for the TB treatment prolongation and TB recurrence rates. By implementing effective management strategies and advancing research, the challenges can be mitigated, arising due to the complex interaction between DM and TB.


Introduction
tuberculosis (tB) infection is a serious global health problem.according to World health Organization (WhO), approximately 5.8 million people were diagnosed with tB and almost 1.5 million people experienced death due to tB [1].Diabetes mellitus (DM) is recognized as one of a strong contributor of tB according to WhO [2].Diabetes mellitus and tB co-existence has become a major health concern worldwide [3]. the presence of DM may be responsible for increasing the severity of tB disease [4].Patients with DM are three times more susceptible to tB as compared to the normal population [3].Diabetes mellitus is becoming more prevalent in various regions of the world [4].the estimated global prevalence of tB-DM comorbid patients was 13.73% [5]. the WhO highlights that DM worsens treatment outcomes for tB and thus causes tB disease progression [6].DM is responsible for extended treatment duration, lower treatment success rates [7], high risks of recurrence or relapse, drug resistance [8] and even death in tB patients [7,9].DM accounts for approximately 11% of deaths in tB patients worldwide [10].controlling tB-DM comorbid conditions can enhance tB treatment success rates by reducing the risk of tB treatment prolongation, death, tB recurrence and drug resistance.it can also reduce the risk of complications caused by DM comorbidity in tB patients, thus improving patient quality of life [11].Due to the presence of DM in tB patients, tB treatment has become a challenge [12].
the WhO and the international Union against tB and lung Disease (iUatlD) framework aims to reduce the dual burden of tB and DM in affected populations through mutual efforts and developing effective treatment approaches [13].thus, the Directly Observed treatment-short course (DOts) Programme was introduced by WhO in 1993 and implemented in 187 countries in 2005 [14].approximately, 4.9 million tB patients were treated under the DOts Programme during the implementation year [14].it makes sure that patients adhere to their medications and aims to enhance tB treatment success rates [15].the DOts strategy includes a combination of four anti-tB drugs (isoniazid, pyrazinamide, ethambutol and rifampicin) for a period of six months to completely eradicate the tB infection [16].the presence of DM makes tB treatment complicated and is responsible for the extended treatment duration [17].it is suggested that the duration of tB treatment may extend from six months to nine months due to the presence of DM [17].thus, it is necessary that DM be confirmed earlier to prevent tB progression in tB patients [18].
Previous systematic review and meta-analysis reported the impact of DM on tB treatment results.there were following limitations present in these earlier systematic review and meta-analysis: unadjusted covariates [19], small sample size, not specifically focused on type 2 DM [20], and no specified therapy guidelines [21].No previous review specifically assessed the impact of type 2 DM on tB patients treatment outcomes including extended treatment duration and recurrence following the DOts Programme for tB treatment.thus, keeping in mind the limitations of the previous systematic reviews and meta-analysis, the objective of the current meta-analysis was to identify and quantify the impact of type 2 DM on treatment outcomes of tB patients treated under the DOts Programme.

Search strategy and study selection
this meta-analysis was performed according to the Preferred Reporting items for systematic Reviews and Meta-analyses (PRisMa) guidelines [22].the databases PubMed, Google scholar, eMBase, Web of science and cochrane library were searched (till June 2023) for studies reporting the DM impact on tB treatment outcomes in which the treatment regimen given to tB patients was DOts therapy recommended by WhO guidelines and the outcomes were defined by WhO criteria.according to PicOs, the following Mesh terms were used to extract relevant articles: 'Diabetes Mellitus' [Mesh] OR 'Diabetes Mellitus, type 2' [Mesh] aND 'tuberculosis' [Mesh] OR 'tuberculosis, Pulmonary' [Mesh] aND 'tB treatment' OR 'tB patients without type 2 Diabetes Mellitus' OR 'treatment Outcome' [Mesh] aND 'Risk Factors' [Mesh] OR 'extended treatment duration' OR 'recurrence' .the references provided at the end of each included study were also searched for inclusion of relevant studies in this meta-analysis.Only english-language articles were considered.

Inclusion criteria
the studies were included in this meta-analysis based on the following PicOs criteria: (1) adult patients with diagnosis of tB, involving both tB-diabetes mellitus type 2 (DM type 2) comorbid patients and alone tB patients.(2) Research articles in which the treatment regimen given to tB patients was DOts therapy recommended by WhO.(3) Research articles comparing DM impact on tB treatment outcomes including extended treatment duration and recurrence in tB-DM comorbid patients vs. tB patients only.(4) Research articles in which patients had their data reported on any of the following tB treatment outcomes, unsuccessful: extended treatment duration and recurrence.
(5) Research articles having a prospective and retrospective cohort, cross-sectional or case-control study design.(6) Original research articles are published in english only.

Exclusion criteria
the studies were excluded from this meta-analysis: (1) if they were non-human studies, studies involving children, pregnant women and studies involving patients with any critical illness.(2) studies involving patients using different anti-tB therapies, patients receiving any type of integrated care.(3) studies analysing type 1 DM patients.(4) studies analysing sputum culture conversion only.( 5) Non-research articles, case reports, case series, models and editorials.( 6) studies for which no full text was available and studies other than english language.
the articles were reviewed on the basis of inclusion and exclusion criteria by two reviewers independently. the third reviewer reviewed the extracted data.conflicts, if any, were then resolved through discussion with a fourth reviewer, if needed.

Data extraction and quality assessment
the data that were extracted from the included studies by two reviewers independently in a data extraction form are as follows: author name, country, publication year of the study, study design, study duration, sample size (tB patients, tB-DM patients), covariates and tB treatment outcome assessed.the data extraction form was then reviewed and verified by a third reviewer, and conflicts were discussed with a fourth reviewer and sorted out for consensus until a final decision was taken.the summaries of the included studies are provided in table 1. the quality of the studies included in this meta-analysis was checked individually by using the Newcastle-Ottawa scale (NOs) [63].the NOs examines potential bias in three different domains: selection of study groups (four points), group comparability (two points) and outcome assessment (three points), assigning greater points for a lower likelihood of bias in each of these domains, up to a maximum of nine points.a score of six or greater indicated less bias and high study quality.

TB treatment outcomes
the tB treatment outcomes analysed in this study were categorized by WhO criteria.the outcomes analysed in this study were unsuccessful outcomes (extended treatment duration and recurrence).since studies used different meanings for recurrence and relapse, we considered them as one-recurrence [64].tB treatment outcomes were defined as extended treatment duration (tB patients with positive sputum culture results even after the fifth month of treatment or later or tB treatment failure patients with progression and worsening of infection in tB patients despite following the prescribed treatment protocol) and recurrence (tB symptoms reappear in tB patients after treatment, even if the patient was cured before) [64].

Statistical analysis
Multivariable logistic regression results for tB unsuccessful treatment outcomes (extended treatment duration and recurrence) were preferably extracted.For pooling the estimates of DM impact on tB treatment outcomes, a fixed-effects model was used to calculate pooled hazards ratio (hR 95% ci).heterogeneity was assessed between studies using I 2 statistics.the studies reported higher heterogeneity if I 2 values were greater than 50%.For tB treatment outcomes, the forest plots were also constructed.all analysis were conducted through licensed statistical software package stata V.16 (stata corp, college station, tX).

Search results
the databases searched a total of 8095 studies.after the removal of 2363 duplicates, 5732 articles were eligible for screening.after thoroughly screening the titles and abstracts, 186 studies were selected for full-text reading.the full text was not available for three studies, even after contacting the authors.a total of 44 studies were selected for inclusion in this meta-analysis.the search strategy is given in Figure 1.

Extended TB treatment duration
the risk of extended treatment duration was reported in 37 studies [2, 7, 23, 25-38, 40-50, 52, 54-58, 60-62].the pooled hR for the impact of DM on extended treatment duration was significant (hR 0.72, 95% ci 0.56-0.83),p ≤ .01 with 47 effect size and moderate heterogeneity (I 2 = 59%) as shown in Figure 2. the subgroup analysis was performed by study design to assess the impact of different study designs on the pooled results.the results remained significant after performing sub-group analysis for extended treatment duration by study design (hR 0.72, 95% ci 0.55-0.84),p ≤ .01 and the heterogeneity was reduced to 21% (I 2 = 21%) as shown in Figure 3.

Recurrence
the risk of tB recurrence was reported in 10 studies [1,17,28,33,43,46,49,52,55,58]. the pooled hR for the impact of DM on recurrence was non-significant (hR 0.931, 95% ci 0.704-1.041),p = .08with 52 effect size. the heterogeneity observed across the studies was moderate (I 2 = 38%) as shown in Figure 4. the subgroup analysis was performed by study design to assess the impact of different study designs on the pooled results.the results were significant for recurrence after performing sub-group analysis by study design (hR 0.862, 95% ci 0.678-0.946),p ≤ .01 and the heterogeneity was reduced to 18% (I 2 = 18%) that showed consistent results across studies as shown in Figure 5.

Composite TB treatment outcomes
the pooled hR (95% ci) for impact of DM on composite tB treatment outcomes (extended treatment duration and reoccurrence) was calculated as 0.76 (95% ci 0.60-0.87),p ≤ .01 with an effect size of 41.18. the heterogeneity observed among the included studies was moderate (I 2 = 55.79%) as shown in Figure 6.

Assessment of risk of bias
this meta-analysis used the NOs to evaluate the risk of bias in each individual study [63].For studies analysing the impact of DM on tB treatment outcomes, the mean score of NOs was seven (out of a maximum of nine points), indicating the high quality of the studies included in this meta-analysis.the risk of bias in the included studies is provided in table 2.

Discussion
this study conducted a meta-analysis to examine the impact of type 2 DM on tB treatment outcomes in pulmonary tB-DM comorbid patients.the analysis extensively reviewed articles specifically focusing on patients with tB treatment outcomes including extended treatment duration and recurrence who were given treatment following the DOts therapy recommended by the WhO.Our findings explored that DM negatively influenced tB treatment outcomes.tB-non-DM patients had a lower risk of extended treatment duration and tB recurrence when compared with tB-DM comorbid patients.this meta-analysis showed a significantly lower risk for extended treatment duration in tB-non-DM comorbid patients as compared to tB-DM patients (hR 0.72, 95% ci 0.56-0.83),p = .01with moderate heterogeneity (I 2 = 59%) across the studies.after performing sub-group analysis by study design, the risk for extended treatment duration remained lower in tB-non-DM comorbid patients as compared to tB-DM patients (hR 0.72, 95% ci 0.55-0.84),p = .01. the results were also found to be significant in previous study and systematic review [19,21,65].But the results were inconsistent with previous studies that reported non-significant results [66][67][68].the study's small sample size could result in insufficient statistical power to detect minor differences.statistical variability may also introduce uncertainty, contributing to non-significant results.Patient characteristics (age, gender, disease state) and healthcare system disparities could mask DM effects on treatment outcomes.Uncontrolled factors like socioeconomic status, healthcare access and adherence might complicate interpretation.these considerations highlight the diverse complexity of the results and suggest that the combined influence of these factors contributed to the non-significant relationship between DM and extended treatment duration in tB-DM comorbid patients [19].
limitations in their study design or methodology might have affected their ability to detect a significant impact of DM on treatment prolongation.the study's sample size and the characteristics of the patient population might not have been adjusted for detecting such an association.similarly, another study might have had challenges related to patient enrolment, data collection or the duration of follow-up, potentially affecting their ability to identify a significant effect [38].additionally, the extended 5-year follow-up period in another study [61] reported confounding variables such as changes in treatment protocols, access to healthcare, or the presence of other comorbidities, which could make it challenging to clearly understand the association between DM and treatment prolongation.these factors highlight the need for accurate research design and interpretation when studying complex health outcomes, in order to obtain significant results.
Our study showed non-significant results for recurrence (hR 0.93, 95% ci 0.70-1.04),p = .08. the results were comparable with a previous study that reported no statistically significant impact of DM on recurrence in tB-DM comorbid patients [69].On sub-group analysis by study design, the results were significant for recurrence (hR 0.86, 95% ci 0.67-0.94),p < .01. it showed that tB-non-DM patients were at lower risk of recurrence when compared with tB-DM comorbid patients.the previous systematic review and meta-analysis also reported a significant DM impact on recurrence in tB-DM comorbid patients [21,70,71].DM weakens the immune system of tB patients, making them more susceptible to tB infection.the pooled hR (95% ci) for impact of DM on composite tB treatment outcomes was 0.76 (95% ci 0.60-0.87),p = .01 in our study.such disparities highlight the need for cautious interpretation.Due to the presence of type 2 DM, the cell-mediated immune functions are compromised in tB patients [72].the type 2 DM if left uncontrolled can also impair the cytokine functions and disrupts type 1 cytokines responses [73].the factors can contribute to unfavourable tB treatment outcomes including death, tB treatment prolongation and tB recurrence emphasizing the importance of future research for a more comprehensive understanding of the tB-DM comorbidity's effect on tB treatment outcome including recurrence and tB treatment prolongation.
When comparing the results of this meta-analysis with previous research, it is noted that different studies have shown both significant and insignificant effects of DM on tB treatment results.these differences were discussed considering the limitations of the studies, like sample size, patient characteristics, methodological differences and uncontrolled factors.still, despite these differences, the main findings of this study have given us a valuable understanding of how DM affects tB treatment outcomes, confirming the harmful impact of DM on different aspects of tB treatment.the strengths of this meta-analysis lie in its comprehensive analysis of a significant number of studies, focusing on a specific patient population treated under DOts therapy.We focused on specific subtypes of DM and tB, providing a more refined understanding of their interaction.however, our study also had several limitations.We included relevant studies from different geographical regions by searching and reviewing the existing literature.there may be the possibility of publication bias, despite our efforts to include a comprehensive set of studies.the biasness may arise from underreporting of negative results or exclusion of studies with negative results leading to potential emphasis on significant findings only and such bias could affect the overall findings of our study.the method of diagnosis for type 2 DM was different in different studies.there was misclassification in the diagnosis of type 2 DM that can affect the results in examining the association between type 2 DM and tB. the glucose levels are increased temporarily during tB but some studies did not emphasize that either DM was diagnosed before tB or during tB or patients can be diagnosed as type 2 DM on the basis of short-term elevation of blood glucose levels.this factor can also impact our findings.the use of statistical methods for controlling diversity in the study designs can make the results unclear.
For future concern, this study highlights the importance of conducting more thorough research with large groups of people, using consistent methods, type 2 DM diagnosis and considering other variables that might affect the results.this would help gain a better understanding of how type 2 DM affects tB treatment outcomes.

Conclusions
a negative impact of DM was found on recurrence and extended treatment duration in tB patients treated with DOts therapy.Diabetes mellitus type 2 is responsible for the tB treatment prolongation and tB recurrence rates.By implementing effective management strategies and advancing research, the challenges can be mitigated arising due to the complex interaction between DM and tB.a.R. all authors have read and agreed to the published version of the manuscript.

Disclosure statement
No potential conflict of interest was reported by the author(s).

Figure 1 .
Figure 1.study selection process in line with the PRisMA guidelines.

Figure 2 .
Figure 2. forest plot for impact of dM on extended treatment duration in TB-dM comorbid patients.

Figure 3 .
Figure 3. forest plot of sub-group analysis for extended treatment duration in TB-dM comorbid patients.

Figure 4 .
Figure 4. forest plot for impact of dM on recurrence in TB-dM comorbid patients.

Figure 5 .
Figure 5. forest plot of sub-group analysis for recurrence in TB-dM comorbid patients.

Figure 6 .
Figure 6.forest plot for composite TB treatment outcomes in TB-dM comorbid patients.

Table 1 .
summaries of the included studies.